Deep Learning Course Projects

Overview

A repository demonstrating work on deep_learning.

This repository contains assignment submissions and code implementations for my Deep Learning course.

Assignments Overview

• Assignment 1: Foundational concepts, likely covering basic neural networks, feedforward architectures, and backpropagation from scratch. Includes code parts (Part1, Part2&3) and a written report.
• Assignment 2: Intermediate topics, focusing on more advanced network designs, optimization, or convolutional layers. Contains three coding parts and a comprehensive PDF report.
• Assignment 3: Advanced deep learning topics. Includes two coding parts and a final assignment report (assignment3.pdf).

Project Structure

Each assignment directory contains:

• Source code divided into parts corresponding to assignment tasks.
• A Report or PDF document detailing the methodology, experiments, and results.
• instruction text files containing the original assignment prompts.

Note: The __pycache__ directories are generated automatically during Python execution and contain compiled bytecode.

Usage

Navigate to specific assignment folders to view the code and reports. Follow any local instruction files inside the directories to run the specific Python scripts.

Setup

git clone <repo-url>
cd deep_learning